Sex Differences Among Older Adults With Bipolar Disorder: Results From the Global Aging & Geriatric Experiments in Bipolar Disorder (GAGE-BD) Project
Bibliographic record
Abstract
OBJECTIVE: Sex-specific research in adult bipolar disorder (BD) is sparse and even more so among those with older age bipolar disorder (OABD). Knowledge about sex differences across the bipolar lifespan is urgently needed to target and improve treatment. To address this gap, the current study examined sex differences in the domains of clinical presentation, general functioning, and mood symptoms among individuals with OABD. METHODS: This Global Aging & Geriatric Experiments in Bipolar Disorder (GAGE-BD) study used data from 19 international studies including BD patients aged ≥50 years (N = 1,185: 645 women, 540 men).A comparison of mood symptoms between women and men was conducted initially using two-tailed t tests and then accounting for systematic differences between the contributing cohorts by performing generalized linear mixed models (GLMMs). Associations between sex and other clinical characteristics were examined using GLMM including: age, BD subtype, rapid cycling, psychiatric hospitalization, lifetime psychiatric comorbidity, and physical health comorbidity, with study cohort as a random intercept. RESULTS: Regarding depressive mood symptoms, women had higher scores on anxiety and hypochondriasis items. Female sex was associated with more psychiatric hospitalizations and male sex with lifetime substance abuse disorders. CONCLUSION: Our findings show important clinical sex differences and provide support that older age women experience a more severe course of BD, with higher rates of psychiatric hospitalization. The reasons for this may be biological, psychological, or social. These differences as well as underlying mechanisms should be a focus for healthcare professionals and need to be studied further.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".